Classifications

• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04B—TRANSMISSION
  • H04B3/00—Line transmission systems
  • H04B3/02—Details
  • H04B3/46—Monitoring; Testing
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
  • H04L1/00—Arrangements for detecting or preventing errors in the information received
  • H04L1/20—Arrangements for detecting or preventing errors in the information received using signal quality detector

Definitions

• the field of the invention is that of digital telecommunications.
• Communication systems can be subject to strong electromagnetic disturbances.
• the noises generated by electromagnetic disturbances can be classified into two broad categories: stationary noises and impulsive noises.
• the measurement method is adapted to the stationary or temporary character of the electromagnetic disturbance.
• a scanning spectrum analyzer is generally used for the study of stationary noise and a digital oscilloscope for the study of impulse noise.
• the conventional operation of a spectrum analyzer is based on a sweep in time of the entire spectrum to be monitored.
• the spectrum analyzer scans the frequencies to obtain the spectral power density of the noise over the entire spectrum.
• This operating principle allows the spectrum analyzer to have a very high sensitivity and a very low internal noise. These two properties make it very suitable for measuring stationary disturbances on telephone lines with sometimes very low levels.
• an impulsive noise is characterized by an amplitude which can be high but especially a duration which is brief. Its duration may be for example a few microseconds for isolated impulsive noise.
• the scanning spectrum analyzer is not suitable as soon as one wants to observe phenomena varying in time. Indeed, to know the spectral density of the overall power of the noise, it is necessary that it does not vary during the scan time of the analyzer.
• the analysis of an impulsive noise, which is a particularly brief phenomenon, will therefore be impossible: the duration of a pulse is much less than the scan time (a few ⁇ versus several ms).
• the digital oscilloscope is a tool for measuring temporal phenomena that allows a measurement of the temporal variations of the observed signal, offering various possibilities for triggering and memorizing signals. This is why it is used to measure impulsive noises.
• a trigger threshold for storing the signals is defined.
• the signal amplitude exceeds this threshold the signal is stored and processed.
• the noises are measured in time. The treatment to know their duration and their amplitude is therefore immediate.
• the threshold must necessarily be above the amplitude of the stationary noise. This implies that impulsive noises whose amplitude is less than that of stationary noise can not be measured by this method.
• Impulsive noises are troublesome for transmissions of xDSL or PLT type, for example, for transmissions for which the frequency characteristics of the transmitted signal must be known and controlled. for good reception of the signal.
• the present invention aims to solve the disadvantages of the prior art.
• the invention proposes a method for measuring impulsive noise in a signal, characterized in that it comprises the steps of:
• variable frequency trigger threshold according to stationary characteristics of the first signal
• an impulsive noise can be measured in a signal comprising a stationary noise, even if the impulsive noise has a smaller amplitude than that of the stationary noise.
• the measurement of such impulsive noises is particularly important for transmissions for which the frequency characteristics of the transmitted signal must be known and controlled to ensure good reception of the signal.
• the trigger threshold is defined in the frequency domain.
• the conversion of the signal in the frequency domain is carried out by a Fourier transform.
• a Fourier transform it is possible to use the fast Fourier transform.
• the conversion of the signal in the frequency domain is carried out in a real-time spectrum analyzer.
• the real-time spectrum analyzer is well suited for converting a signal in the frequency domain.
• the triggering threshold is defined from a stationary noise measurement in the first signal.
• the trigger threshold is adapted to the processed signal. As long as the processed signal includes only stationary noise, the triggering threshold is not exceeded and no impulsive noise is sought. On the contrary, as soon as the triggering threshold is reached, it indicates the presence of an impulsive noise and the treatment continues to measure this impulsive noise.
• the trigger threshold is a mask located above the first signal.
• the triggering is performed in a relatively simple manner, by comparing the second signal with the mask, in the frequency domain.
• a plurality of first signals is measured and converted in the frequency domain, the frequency-variable trigger threshold then being defined as a function of the average of the plurality of first converted signals.
• the invention also relates to a device for measuring impulsive noise in a signal, characterized in that it comprises:
• AS - Conversion means
• the device provides advantages similar to those of the previously presented method.
• the various steps of the methods according to the invention are determined by instructions of computer programs.
• the invention also relates to a computer program on an information medium, this program being capable of being implemented in a computer, this program comprising instructions adapted to the implementation of the steps of a process as described above.
• This program can use any programming language, and be in the form of source code, object code, or intermediate code between source code and object code, such as in a partially compiled form, or in any other form desirable shape.
• the invention also relates to a computer readable information medium, and comprising instructions of the computer programs as mentioned above.
• the information carrier may be any entity or device capable of storing the program.
• the medium may comprise storage means, such as a ROM, for example a CD ROM or a microelectronic circuit ROM, or a magnetic recording medium, for example a floppy disk or a disk. hard.
• the information medium may be a transmissible medium such as an electrical or optical signal, which may be conveyed via an electrical or optical cable, by radio or by other means.
• the program according to the invention can be downloaded in particular on an Internet type network.
• the information carrier may be an integrated circuit in which the program is incorporated, the circuit being adapted to execute or to be used in the execution of the method in question.
• FIG. 1 represents an embodiment of a measurement method according to the invention
• FIG. 2 represents an exemplary signal to be processed according to the invention, in the time domain
• FIG. 3 represents the same signal example to be processed according to the invention, in the frequency domain
• FIG. 4 represents the signal being processed according to the invention, in the frequency domain
• FIG. 5 represents an embodiment of a step of the method according to the invention
• FIG. 6 represents the impulsive noise signal determined according to the invention.
• FIG. 7 represents an embodiment of measuring device according to the invention.
• the method for measuring impulsive noise in a signal S comprises steps E1 to E5.
• Step E1 is the measurement of at least a first signal S by a real-time spectrum analyzer.
• This first signal S is represented in time form in FIG. 2. It comprises stationary noise and is capable of including impulsive noise.
• the stationary characteristics of the signal are known.
• the first signal S of FIG. 2 comprises only stationary noise in a preferred embodiment.
• first signal S is indicated as being measured at this stage, but a plurality of first signals S can also be measured, for example by making several successive passes by means of the time spectrum analyzer. real.
• the next step E2 is the conversion of the first signal S into the frequency domain, for example by applying a FFT fast fourier transform.
• FIG. 3 represents the first signal S after conversion in the frequency domain. It can be seen that the amplitude of the first signal S is higher for the low frequencies than for the higher frequencies.
• the next step E3 is the definition of a tripping threshold, in the frequency domain, as a function of stationary characteristics of the signal.
• this trigger threshold is variable in frequency in order to take into account the stationary characteristics of the signal.
• a frequency mask M is defined whose amplitude is situated above that of the first signal S.
• this frequency-variable trigger threshold is defined as a function of these first signals S, for example as a function of the average of these first signals S.
• the frequency mask M above may be defined with an amplitude above that of the average of these first signals S.
• This second signal S 'to be analyzed thus comprises stationary noise, similar to that of the first signal S, and impulsive noise.
• the impulsive noise has a smaller amplitude than that of the stationary noise, so that the temporal representation of the second signal S ' is similar to that of the first signal S ( Figure 2).
• Impulsive noise is not directly detectable in the time domain and is somehow hidden in the stationary noise.
• the steps E41 to E43 are implemented:
• the second signal S ' is measured (step E41) by a real-time spectrum analyzer, similarly to the aforementioned step E1.
• this second signal S ' is then converted into the frequency domain (step E42), similarly to the aforementioned step E2, for example by applying a Fast Fourier Transform FFT.
• the second signal S ' is memorized as soon as the measured noise level reaches or exceeds the frequency mask M (step E43), which results in obtaining a memorized signal S "having frequency components only on certain Part of the spectrum
• the triggering of the storage is therefore based on a frequency analysis of the second processed signal S.
• the stored signal S " is stored in the time domain.
• FIG. 4 is an example of a spectral representation of the memorized signal S ".
• the second signal S ' comprises a stationary noise, substantially identical to that of the first signal S represented in FIGS. 2 and 3, and an impulsive noise which The signal S 'is substantially identical to the signal S in the low frequencies, and it is distinguished by the two peaks which are located in the high frequencies .
• the amplitude of the two peaks is less than the amplitude.
• maximum signal S 'but is greater than that of the mask M frequencies carrying these peaks, there is thus spectral detection of the presence of impulsive noise by means of the stored signal S "corresponding to these two peaks.
• the next step E5 is the processing of the stored signal S "after spectral detection of the presence of the impulsive noise
• the memorized signal S" is a time signal whose duration is 2 ms. It has five acquisition frames of 1024 points each.
• a real-time spectrum analyzer works typically on frames of 1024 points, but of course, the invention is not limited to this embodiment.
• the processing comprises substeps E51 to E55:
• step E51 a frame of 1024 points is considered and the fast Fourier transform FFT is calculated.
• the result is a signal in the frequency domain.
• the following step E52 is a high-pass filtering of the signal obtained in the preceding step.
• the purpose of high-pass filtering is to eliminate the lower part of the spectrum, for which the signal has a higher amplitude than the rest of the spectrum. This lower part of the spectrum masks impulsive noises.
• the result is a filtered Sf signal, freed of its low frequencies.
• the next step E53 is the calculation of the inverse Fourier transform of the previously filtered signal, to obtain a temporal representation of the filtered signal.
• the maximum is the norm of the result vector of the inverse Fourier transform.
• the maximum is the largest value between the norm of the result vector of the inverse Fourier transform and the maximum determined at the previous iteration. The determination of the maximum energy E max makes it possible to determine the amplitude of the signal at a time t and thus to reconstitute the temporal envelope of the signal representative of the impulsive noise.
• step E55 is a transition to the next frame in the memorized signal, until all the frames have been processed. As long as at least one frame remains to be processed, step E55 is followed by step E51.
• FIG. 6 shows an example of impulsive noise B extracted from the signal S 'which contained a stationary noise and an impulsive noise of amplitude less than that of the stationary noise.
• impulsive noises are generated by household appliances, for example in a dwelling. These impulsive noises are then conveyed by the electric cables and can couple on the telephone cables.
• the quality of service may be degraded, which results in phenomena of pixelation of the image or "freezing" of the image.
• the interleaving delay and the target noise margin for ADSL can be determined according to the noise impulsive.
• a device 1 for measuring impulsive noise in a signal comprises:
• means for converting the signal in the frequency domain means for defining a frequency-variable trigger threshold as a function of stationary characteristics of the signal;
• the device 1 implements the steps previously described.
• it comprises an AS real-time spectrum analyzer coupled with a computing device, typically having the structure of a computer.
• the real-time spectrum analyzer AS receives the signal to be processed and performs the steps of conversion, definition of a trigger threshold and of memorizing the signal. The subsequent processing is performed by the computing equipment.
• Such equipment comprises a memory January 1 comprising a buffer memory, a processing unit 12, equipped for example with a microprocessor, and driven by the computer program 13, implementing the method according to the invention.
• the code instructions of the computer program 13 are for example loaded into a RAM memory before being executed by the processor of the processing unit 12.
• the processing unit 12 receives as input the signal stored by the real-time spectrum analyzer after triggering.
• the microprocessor of the processing unit 12 implements the steps of the method described above, according to the instructions of the computer program 13, for measuring the impulsive noise in the signal.

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• Engineering & Computer Science (AREA)
• Computer Networks & Wireless Communication (AREA)
• Signal Processing (AREA)
• Quality & Reliability (AREA)
• Noise Elimination (AREA)
• Measurement Of Resistance Or Impedance (AREA)

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• 2010
  • 2010-12-20 FR FR1060820A patent/FR2969435A1/fr not_active Withdrawn
• 2011
  • 2011-12-19 US US13/996,365 patent/US20140010273A1/en not_active Abandoned
  • 2011-12-19 WO PCT/FR2011/053059 patent/WO2012085431A1/fr active Application Filing
  • 2011-12-19 EP EP11817397.0A patent/EP2656531B1/de active Active

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